ABSTRACT
In Slovenia, patients report difficulties registering with a family doctor (FD), even in dense urban areas, since the patient-to-FD ratio is well below the EU average and not improving. Moreover, public primary healthcare providers (PCP) report difficulties with the financial liquidity that endangers the regular payment of employed FDs' salaries and constantly call for additional budget funding in the healthcare sector, especially after the COVID-19 pandemic crisis. It is therefore questionable, whether or not the PCP, which perform economic activity under the EU standards, respect human rights of all the stakeholders in the healthcare sector. Therefore, in this paper, I analyse the existing regulations on the public financing of FDs in Slovenia that seems to pose significant problems to patients' timely access to health care and does not facilitate the FDs' goal of delivering the patients' constitutional right to healthcare services. I discuss some better alternative solutions that would promote the patients' right to effective primary healthcare, attract more medical students to specialise in family medicine and consolidate the fiscal sustainability of the primary healthcare sector, which is at grave risk of collapse due to a dysfunctional healthcare payment and delivery system. Copyright © 2022 Inderscience Enterprises Ltd.
ABSTRACT
COVID-19, also known as 2019-nCoV, is no longer a pandemic but an endemic disease that has killed many people worldwide. COVID-19 has no precise treatment or remedy at this time, but it is unavoidable to live with the disease and its implications. By quickly and efficiently screening for covid, one may determine whether or not one has COVID-19 and thus limit the financial and administrative burdens on healthcare systems. Research has shown that predictions which use many variables in order to predict the likelihood of infection have been established. Due to the world's inadequate healthcare systems, this fact places significant strain on these countries' healthcare systems, particularly in emerging nations. While there is no proven antiviral medication method or licensed vaccine that can eliminate the COVID-19 pandemic, there are other potential options that would alleviate both healthcare systems and the economy from the weight of the virus. Non-clinical approaches like machine learning, data mining, deep learning, and other artificial intelligence approaches are among the most promising approaches for use outside of a clinical setting. To make diagnosis and prognosis for patients with the 2019-NCoV pandemic easier, use these options. Additionally, artificial intelligence systems, such as decision trees, support vector machines, artificial neural networks, and naïve Bayesian models, are validated using a positive and negative COVID-19 case dataset. To establish the degree of connection between dependent characteristics, correlation coefficients between different dependent and independent variables were investigated. During preparation, the model was trained for 80% of the time, while at the same time, it was tested for 20% of the time. Based on the success evaluation, the Random Forest had the best precision of 94.99%. © 2021 IEEE.